        CRISTINA SERBAN (GHERGHINA), CARMEN MAFTEI, COSMIN FILIP Faculty of Civil Engineering “Ovidius” University of Constanta 124 Mamaia Av. ROMANIA serban.cristina@univ/ovidius.ro , cmaftei@univ/ovidius.ro , cosminfilip@univ/ovidius.ro Abstract: The paper describes a service for using on Computational Grids that addresses the computation of Normalized Difference Vegetation Index (NDVI), Normalized Difference Snow Index (NDSI) and Normalized Burn Ratio (NBR) based on satellite imagery. We consider the service will be greatly useful and convenient for those who are studying the growth and vigor of green vegetation by using environmental remote sensing, and have typical workstations, with no special computing and storing resources for computationally intensive satellite image processing and no license for a commercial image processing tool. : Computational Grid, Environmental Remote Sensing, Multi/spectral indices   Grid computing offers the potential of virtual organizations groups of people both geographically and organizationally distributed working together on problems, sharing computers and other resources such as databases and experimental equipment. The challenge with a Grid infrastructure is to be able to dynamically locate, manage, and assure quality performance from participating systems. Grid technology has the potential to significantly impact many areas of study with heavy computational requirements, like chemistry, physics, genetics, encryption, math, modeling, animations, digital video production, image processing, etc. Vegetation indices (VI) are combinations of spectral measurements in different wavelengths as recorded by a radiometric sensor. They aid in the analysis of multispectral image information by shrinking multidimensional data into a single value. Huete (1994) defined vegetation indices as: “dimensonless, radiometric measures usually involving a ratio and/or linear combination of the red and near/ infrared (NIR) portions of the spectrum. VI’ s may be computed from digital counts, at satellite radiances, apparent reflectances, land/leaving radiances, or surface reflectances and require no additional ancillary information other than the measurements themselves. “. Vegetation indices serve as indicators of relative growth and vigor of green vegetation, and are diagnostic of various biophysical vegetation parameters. In this study, we describe a service for using on Computational Grids, that addresses the computation of Normalized Difference Vegetation Index (NDVI), Normalized Difference Snow Index (NDSI) and Normalized Burn Ratio (NBR) based on satellite imagery. This service will extend the functionality of the web platform described in [2], which consists of already implemented Grid services that compute various environmental remote sensing algorithms applied over the Dobrogea region. This paper is organized in 4 sections. The first section is Introduction and the second presents the Input Data Sets and the Methodology. Next, in section 3, we describe the service that uses the Computational Grid and the experimental results. Conclusion and further work are approached in section 4.       The Dobrogea region was selected as the case study area due to its high exposure to aridity, drought and even desertification phenomenon. Dobrogea is a region situated in the South – East of Romania, between the Black Sea and the lower Danube River – Fig.1.        The Landsat program has been operating since 1972, allowing for uninterrupted observation of Earth throughout this period and making it an invaluable tool for longitudinal studies of environmental problems. The satellite's sunsynchronous orbit takes Computational Engineering in Systems Applications (Volume II) ISBN: 978-1-61804-014-5 120